StatsPAI_skill

Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW + g-formula + TMLE triplet, Mendelian randomization, KM/AFT survival, E-value sensitivity, STROBE/TRIPOD reporting) — OR in ML causal inference style (DML, S/T/X/R/DR meta-learners, causal forest, Dragonnet/TARNet/CEVAE, BCF, CATE distribution, policy learning, conformal causal, fairness audit, causal discovery) — OR in distributional / gap-decomposition style (Oaxaca–Blinder `sp.oaxaca`, Kitagawa `sp.kitagawa_decompose`, DiNardo–Fortin–Lemieux `sp.dfl_decompose`, Gelbach `sp.gelbach`, Fairlie `sp.fairlie`, RIF / FFL `sp.rif_decomposition`, all reachable through the `sp.decompose` dispatcher). Also covers exporting multi-column regression tables to Word / Excel / LaTeX (Stata outreg2 / esttab / R modelsummary equivalent) and bundling an entire replication appendix into one .docx / .xlsx / .

请帮我安装这个 Agent Skill：https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/00-Full-empirical-analysis-skill_StatsPAI

1. 先读取该目录下的 SKILL.md 和其他文件，检查是否有可疑内容（执行未知脚本、读取密钥、向外发送数据等），用中文告诉我它会做什么、需要哪些权限；
2. 等我确认后，再把整个目录安装到 ~/.claude/skills/statspai-skill/（如果你不是 Claude Code，安装到你自己约定的 skills 目录）；
3. 安装后告诉我怎么触发它。

git clone --depth 1 --filter=blob:none --sparse https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git /tmp/statspai-skill-src
cd /tmp/statspai-skill-src && git sparse-checkout set "skills/00-Full-empirical-analysis-skill_StatsPAI"
mkdir -p ~/.claude/skills && cp -r "skills/00-Full-empirical-analysis-skill_StatsPAI" ~/.claude/skills/statspai-skill

Skill 可以让智能体执行脚本。安装第三方 Skill 前务必看一遍内容，详见「安全」一课。